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SKILL.md

expert-panel

Agent skill fromericosiu/ai-marketing-skills

Score, evaluate, and iteratively improve any content or strategy using an auto-assembled panel of domain experts. Handles copy, sequences, landing pages, strategy docs, titles, charts, recruiting evaluations, or anything else that needs a quality gate. Recursively iterates until all scores hit 90+ (max 3 rounds). Use when asked to: "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "which version is better", "expert score", "evaluate this copy/strategy/page", or when another skill needs a quality gate on its output. Also triggers on: "score this landing page", "expert panel these email variants", "rate this headline", "panel these charts".

How to install expert-panel

install expert-panel
# install the ai-marketing-skills pack with the skills CLI
npx skills add ericosiu/ai-marketing-skills

# or add only this skill to Claude Code: copy the folder

content-ops/

# into

~/.claude/skills/content-ops/ (all projects)

.claude/skills/content-ops/ (one project)

content-ops/SKILL.md

MITFull file
1## Preamble (runs on skill start)
2
3```bash
4# Version check (silent if up to date)
5python3 telemetry/version_check.py 2>/dev/null || true
6
7# Telemetry opt-in (first run only, then remembers your choice)
8python3 telemetry/telemetry_init.py 2>/dev/null || true
9```
10
11> **Privacy:** This skill logs usage locally to `~/.ai-marketing-skills/analytics/`. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See `telemetry/README.md`.
12
13---
14
15# Expert Panel
16
17General-purpose scoring and iterative improvement engine. Auto-assembles the
18right experts for whatever is being evaluated, scores it, and loops until 90+.
19
20---
21
22## Step 1: Intake — Understand What's Being Scored
23
24Collect or infer from context:
25
261. **Content/artifact** — The thing(s) to score (paste, file path, or URL)
272. **Content type** — Copy, sequence, landing page, strategy, title, chart, candidate eval, etc.
283. **Offer context** — What's being sold/promoted? To whom? What domain/industry?
294. **Variants** — Are there multiple versions to compare? (A/B/C)
305. **Source skill** — Is this output from another skill? (e.g., cold-outbound-optimizer)
31 If yes, note the source for feedback-to-source routing in Step 6.
32
33If context is obvious from the conversation, don't ask — just proceed.
34
35---
36
37## Step 2: Auto-Assemble the Expert Panel
38
39Build a panel of **7–10 experts** tailored to the content type and domain.
40
41### Assembly rules
42…

Excerpt shown under the repository's MIT license.

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